DocumentCode :
3270584
Title :
Subregion based local descriptor
Author :
Xiaojie Dong ; Erqi Liu ; Jie Yang
Author_Institution :
Inst. of Image Process. & Pattern Recognition, Shanghai Jiaotong Univ., Shanghai, China
fYear :
2013
fDate :
15-18 Sept. 2013
Firstpage :
250
Lastpage :
254
Abstract :
A novel distinctive descriptor named MSOGH is proposed, which is able to well represent the interest region and is robust to photometric transformations and geometric transformations. According to intensity order, subregions are firstly constructed. Then feature descriptor of the subregion is computed by point permutation of the sample points in each subregion. Finally, feature descriptor of the region is formed by concatenating all subregion feature descriptors. The discriminative power of the proposed descriptor is compared with 5 major existing region descriptors (MROGH, SIFT, GLOH, PCA-SIFT and spin images). Extensive experimental results show that the proposed descriptor achieves better performance than state-of-the-art descriptors.
Keywords :
feature extraction; image representation; GLOH; MROGH; MSOGH; PCA-SIFT; geometric transformations; intensity order; interest region representation; photometric transformations; point permutation; spin images; subregion based local descriptor; subregion feature descriptor; Color; Detectors; Feature extraction; Histograms; Robustness; Standards; Vectors; Image Matching; Local Descriptor; Performance Evaluation; Subregion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location :
Melbourne, VIC
Type :
conf
DOI :
10.1109/ICIP.2013.6738052
Filename :
6738052
Link To Document :
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